Most companies are subject to audit, be these quality or financial. Audits, as defined in the internal standards for quality audits, ISO 19011:2018—Guidelines for auditing management systems, are a “systematic, independent and documented process for obtaining audit evidence [records, statements of fact or other information which are relevant and verifiable] and evaluating it objectively to determine the extent to which the audit criteria [set of policies, procedures or requirements] are fulfilled.”
Audit process
The audit process traditionally involves trained auditors visiting a workplace and undertaken a formal review of documentation and interviewing staff. This may also extend to a review of computerized systems. Where financial audits are conducted, the auditors will be seeking to determine whether there has been financial fraud. Here the auditor’s role is to conduct an audit in such a manner as to obtain reasonable assurance that the financial statements, taken as a whole, are free from material misstatements, whether due to fraud or error. As systems become more sophisticated, so do techniques designed to obscure financial information.
Big data analysis
This is where big data analysis can come in, according to new research from Bond Business School, Australia. The research has found that auditing is lagging behind in the use of valuable big data techniques and hence there are many opportunities for greater use of big data techniques in auditing. Big data refers to structured or unstructured data sets that are commonly described according to the four Vs: Volume, Variety, Velocity, and Veracity.
Because the volume of company financial data is increasingly broad, and found in different data formats (variety); and moves in and out of the organization so fast (velocity) and change dramatically over time (veracity), new computerized techniques are required to make sense of the workings of the modern firm, in terms of drawing meaningful inferences from the variety of types of data. There are many big data approaches; one suitable for examining financial data are tree models. These are based on non-parametric models that are built in a recursive process of splitting the data into homogenous groups.
Case for further research
While the application of big data is in its infancy for financial audits, more research is needed to further align theory and practice in this area. The findings have been published in the Journal of Accounting Literature, in a paper titled “Big data techniques in auditing research and practice: Current trends and future opportunities.”
